The difference between Data Science, Artificial Intelligence and Machine Learning

It is very common for data science, or data science, to be seen in association with artificial intelligence and machine learning, as they are often worked together.
But, make no mistake, each one is responsible for a different function.
Machine learning:
It is a set of methods used for the automatic identification of patterns, by an algorithm, which can be used to make decisions or carry out actions, such as identification of paths, facial recognition, among others.
Artificial intelligence:
Artificial intelligence is the use of computers and algorithms to perform mundane tasks typically performed by humans, such as driving cars, approving credit applications, or controlling enemy characters in a video game.
Data Science:
Area of study in which we can obtain insights through data using data analysis and visualization, machine learning and artificial intelligence resources. We may identify information such as purchase patterns, in-app behavior patterns, and more.
Who are data professionals?
There is often a certain confusion regarding the professionals who are part of the data area.
Data scientist.
The professional who works as a data scientist has knowledge and experience in computer science, statistics and mathematics, as one of the broadest activities in the data area. His responsibilities are very focused on analyzing large volumes of data and gaining insights.
Data Analyst.
The professional who works as a data analyst is responsible for collecting, analyzing and interpreting the information and insights obtained through the data. Its recommendations are critical to data-based decisions made by other sectors of the company.